Machine learning-based biomechanical analysis for thoracic aortic aneurysm rupture risk assessment
Active Project Grant Awarded Last action
- Award ID
- R01HL158829
- Recipient
-
University Of Miami UEI RQMFJGDTQ5V3 Part of University Of Miami
- Awarding agency
-
National Heart Lung and Blood Institute
National Institutes of Health, Department of Health and Human Services
- Obligated
- $8,911,532
Award facts
- Assistance listing
- 93.837 Cardiovascular Diseases Research
- Completion date 98% complete
- Funding
-
- $7,842,700.00 Federal
- $1,068,832.00 Non-federal
- Place of performance
- South Miami, FL 33146, USA
Award details come from USAspending.gov.
Description
- Abstract
- Aortic aneurysm disease ranks consistently in the top 20 causes of death in the U.S. Population. Thoracic aortic aneurysm (TAA) is a leading cause of death in adults. The progression of TAA is a silent process, yet rupture/dissection can occur suddenly, which often causes death. The deadly events are preventable by elective surgical repair, and the current criterion for surgical intervention states that surgery should be performed when TAA maximum diameter reaches 5 to 5.5 CM. However, this criterion cannot assess the risk of smaller taas (diameter=5CM). IT is estimated that there are millions of TAA patients in the U.S. With smaller taas, and these patients are unfortunately ignored by the current criterion. Thus, in this project, we propose an innovative approach of integrating machine learning (ML) and computational biomechanics for risk assessment of smaller taas. To achieve this goal, we will develop (1) ML models for automated thoracic aorta geometry reconstruction from 3D clinical CT images, which will enable a fast and streamlined analysis of TAA risk, (2) ML models for realtime TAA stress analysis, and (3) a probabilistic risk index that fuses the measured and computed patient characteristics (e.g. geometry, stress, material strength, etc) and takes into account uncertainties from different sources. The proposed approach will be developed and validated on an existing dataset of 1000 patients and a new dataset to be assembled from a longitudinal follow-up study of 600 patients, which will be the first large-scale study of machine learning-based biomechanical analysis for TAA risk assessment. This study will lead to a breakthrough in the fields of cardiovascular computational modeling and applied machine learning, provide new insights on how to better assess TAA risk, and reduce death by the silent and sudden killer of TAA disease.
Transactions
| Action | Federal | Non-federal | Date |
|---|---|---|---|
| Amendment | $15,469 | $0 | |
| Amendment | $489,923 | $0 | |
| Amendment | $489,923 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $41,255 | $0 | |
| Amendment | $41,255 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $51,570 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $464,137 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $464,137 | $0 | |
| Amendment | $604,695 | $0 | |
| Amendment | $604,695 | $604,695 | |
| Original award | $604,695 | $0 |
Show all 24
Subawards
| Subrecipient | Amount | Awarded |
|---|---|---|
| Yale Univ | $506,660 | |
| Sutra Medical Inc. | $599,885 |
Quick answers
Who received award R01HL158829?
R01HL158829 was awarded to University Of Miami by National Heart Lung and Blood Institute (National Institutes of Health) on December 3, 2021.
How much is award R01HL158829 worth?
$8,911,532 has been obligated on R01HL158829: $7,842,700 in federal funding and $1,068,832 in non-federal funding.
On GovTribe
See this award's full record
- Every transaction and subaward
- The recipient's other awards and teaming partners
- Similar grant awards
- Ask GovTribe AI about this award